A Robust Secure and High Capacity Image Watermarking Scheme for Information Exchange in Distributed Collaborative Networked Intelligent Measurement Systems

Due to the rise in many industrial environment applications involving distributed networked collaborative intelligent measurement systems, intelligent monitoring and multi-sensor information exchange of private information, digital image information security and hidden image authentication, tampering detection, correction, and automatic intelligent self-recovery have become critical concerns. Towards that end, there is a need for more secure, efficient, and robust-to-unauthorized-tampering digital image watermarking, information hiding and authentication schemes. In our prior work, we introduced non-blind watermarking schemes where the carrier and watermark images are available at the receiver's end. We also proposed a double-blind scheme where both the carrier and the watermark images are not available at the receiver's end, but at the expense of possible lower pixel tampering, authentication and automatic intelligent self-correction ability. This paper proposes a blind wavelet-based, high capacity, secure digital watermarking and information hiding scheme with higher tampering localization and authentication that nullifies the need to have the carrier image available at the receiving end. The proposed scheme also increases robustness to image authentication and automatic self-recovery and correction compared to our prior double-blind scheme. The scheme is high capacity and sustains hiding secret hidden and watermarking images of the same full size as an arbitrary-sized carrier image. One of the benefits of the blind watermarking scheme is that it allows usage of varying and arbitrary carrier images that are unknown and unavailable anywhere, including the receiver's end. This is to prevent hackers' recognition of a familiar carrier image and their potential unauthorized tampering. Here, in this paper, two grayscale images are inserted in a colored carrier image. Here the watermark image is used for authentication and tamper localization. The second image is used as ownership or encoded secret hidden message image. The Arnolds Transform is used to introduce added security to a hidden image. The proposed scheme uses an embedded correction matrices mechanism for the extracted hidden information self-recovery from various tampering and digital attacks by unauthorized hackers.

A secure high capacity full-gray-scale-level multi-image information hiding and secret image authentication scheme via Tchebichef moments

In order to improve the security of ciphertext image in transmission, a scheme of using neural network is proposed to restore the encryption-hiding images by using chaotic iris phase mask and double random phase encoding encrypted. To improve encryption performance, we replace the double random phase with chaotic iris phase masks. Firstly, the plaintext image is encrypted by improved double chaotic iris phase masks encoding, and the ciphertext image is generated. Then the ciphertext image is hidden into the carrier image through the Least Significant Bit (LSB) algorithm. It can avoid the detection to a certain extent. And a large number of hidden-plaintext image pairs are produced as a dataset. Secondly, the neural network is built in the process of continuous training and testing. The neural network selected in this paper is residual network (ResNet). The neural network to learn the logical relationship between input and output more efficiently, and successfully recovered the corresponding plaintext image. Finally, the trained neural network can fit the mapping relationship between the hidden image and the plaintext image. When decrypting, it is not necessary to extract the ciphertext image from the hidden image first and then decrypt it. This scheme can directly realize the decryption of hidden images. The paper elaborates the encryption, hiding and decryption process of the scheme in detail. Simulation experiments show that the scheme is feasible and has good robustness.

This paper proposes a novel scheme combining Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) for image watermarking. The watermarking image is separated by two parts randomly, then they are embedded into the sub-bands obtained from the original image in DWT domain by modifying the singular value. SVD is applied twice in this scheme.The use of the threshold of Just Noticeable Distortion (JND) based on human visual model determines the embedding strength and position of the watermark, the digital adaptive watermarking algorithm in a combinational domain is realized. The experimental results show that the proposed scheme has a good invisibility and performance of robustness for common attacks, simultaneously enhances the embedding capacity and security.

Watermarking techniques have been proposed as an effective method to protecting the copyright of multimedia data. At present, a large proportion of the watermarking algorithms embed the grey image into the carrier image. In this paper, a watermarking algorithm for color images based on wavelet analysis is proposed. The algorithm scrambled the original watermark image in pretreatment, and used the wavelet transform to process the carrier image and the scrambled watermark image. Then the color watermarked image was embedded into the low-frequency discrete wavelet coefficient of the color carrier image. The experimental results demonstrate that the algorithm can assure the security of the watermark image, and the watermark image has good invisibility and strong robustness for common signal processing and attack.

This paper presented a new watermarking method for convert communication and copyright protection. For improving the transparency and robustness of watermarking or information hiding, a visual model was employed to calculate the block based just noticeable difference (JND), and the three detail sub-bands of block discrete wavelet transform (DWT) were selected for embedding objects. Firstly, a watermark sequence binarized from a text information file or image file was encoded by redundant encoding and scrambled chaotically. Then, an image block was selected each time from the carrier image, and transformed by DWT. And then according to the JND and the watermark code, the coefficients at same position of three detail sub-bands were adjusted to hide the information. Lastly, the inverse DWT was executed to get the information hidden image. The experimental results show that the hidden information is invisible, and the algorithm is robust to general image processing operations. The conclusion is that the algorithm is effective and practical.

This paper addresses an Arnold Transform based gray image embedding in video using Discrete Wavelet Transform (DWT). In the proposed scheme, the video is authenticated with different parts of watermark by using histogram-based scene change technique. Each frame is estranged into three planes. DWT is applied to selective plane in each frame to putrefy into sub-bands. The chosen secrete image is separated into 8-bit planes. Bit plane image is further scrambled using an Arnold transform to get high protection of watermark. In this scheme, embedding is done in mid and high-frequency coefficients of DWT without mortifying the perceptual quality of video. Hidden image is extracted from the marked video by following the inverse processing steps. Robustness is tested by subjecting the marked video to various video processing and image processing attacks. Simulation results show that the proposed scheme is highly resistant to frame averaging, frame dropping, and noise attacks.

We propose in this paper a discrete wavelet transform (DWT) based digital image watermarking technique. For embedding process, we consider the watermark signal as a binary sequence which is embedded to the high (HL and HH) frequency band of the blue channel. For detecting process, the correlation between the high frequency band DWT coefficients of the watermarked image and the watermark signal is compared with the predefined threshold to determine whether the watermark is present or not. The experimental results show that the method is comparatively robust to several attacks such as rotation, scaling, JPEG compression, cropping, and multiple watermarking.

An enhanced hybrid image watermarking scheme for security of medical and non-medical images based on DWT and 2-D SVD

In this paper, a blind image watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed. In this scheme, DWT is applied on ROI (region of interest) of the medical image to get different frequency subbands of its wavelet decomposition. On the low frequency subband LL of the ROI, block-SVD is applied to get different singular matrices. A pair of elements with similar values is identified from the left singular value matrix of these selected blocks. The values of these pairs are modified using certain threshold to embed a bit of watermark content. Appropriate threshold is chosen to achieve the imperceptibility and robustness of medical image and watermark contents respectively. For authentication and identification of original medical image, one watermark image (logo) and other text watermark have been used. The watermark image provides authentication whereas the text data represents electronic patient record (EPR) for identification. At receiving end, blind recovery of both watermark contents is performed by a similar comparison scheme used during the embedding process. The proposed algorithm is applied on various groups of medical images like X-ray, CT scan and mammography. This scheme offers better visibility of watermarked image and recovery of watermark content due to DWT-SVD combination. Moreover, use of Hamming error correcting code (ECC) on EPR text bits reduces the BER and thus provides better recovery of EPR. The performance of proposed algorithm with EPR data coding by Hamming code is compared with the BCH error correcting code and it is found that later one perform better. A result analysis shows that imperceptibility of watermarked image is better as PSNR is above 43 dB and WPSNR is above 52 dB for all set of images. In addition, robustness of the scheme is better than existing scheme for similar set of medical images in terms of normalized correlation coefficient (NCC) and bit-error-rate (BER). An analysis is also carried out to verify the performance of the proposed scheme for different size of watermark contents (image and EPR data). It is observed from analysis that the proposed scheme is also appropriate for watermarking of color image. Using proposed scheme, watermark contents are extracted successfully under various noise attacks like JPEG compression, filtering, Gaussian noise, Salt and pepper noise, cropping, filtering and rotation. Performance comparison of proposed scheme with existing schemes shows proposed scheme has better robustness against different types of attacks. Moreover, the proposed scheme is also robust under set of benchmark attacks known as checkmark attacks.

With the rapid advancement of intelligent transportation systems (ITS), secure processing of color traffic images has become critical for traffic management, safety monitoring, and flow analysis. However, ITS are increasingly susceptible to malicious attacks and data tampering. To address this, we propose an advanced visual encryption method specifically for color traffic images. Our approach employs discrete wavelet transform (DWT) to represent images sparsely, followed by dynamic three‐dimensional spiral disruption for encryption. Chaotic systems then compress the encrypted data, embedding it into a carrier image via least significant bit (LSB) techniques. Experimental results demonstrate robust visual security, achieving a peak signal‐to‐noise ratio (PSNR) above 42 dB, strong resilience against common attacks, and a substantial a key space of 2 512 ×10 60 , effectively resisting brute‐force attacks. Neighboring pixel correlation coefficients drop below 0.15, compared to original images (>0.87), and under shear resistance attack with 128×128 data loss, PSNR remains above 23 dB. Additionally, employing P‐tensor product compressed sensing significantly reduces measurement matrix dimensionality, enhancing transmission efficiency. This method offers a viable solution for secure storage and transmission in modern ITS, significantly bolstering privacy and system robustness. The implementation is available at: https://gitee.com/zhangshuo‐aly/image‐encryption .

A visually meaningful image encryption scheme with an asymmetric structure based on the discrete wavelet transform (DWT) and Schur decomposition is proposed in this study. First, the RSA algorithm is used to generate the initial values for the chaotic system to produce the random sequence. Then, both scrambling and diffusion operations are performed on the plain image to obtain the preencrypted image. Moreover, the Schur decomposition is applied on the preencrypted plain image to obtain the upper triangular and orthogonal matrices. Second, the cover image is scrambled followed by a DWT operation. Four subbands are then formed, namely, LL, HL, LH, and HH. Finally, the former upper triangular matrix and orthogonal matrix are embedded into subbands LH and HH produced by the cover image. After the application of the inverse DWT and inverse scrambling operation, the final visually meaningful cover image embedded with a secret plain image can be obtained. No one can identify any useful information about the plain image from the final embedded cover image, nor can anybody know that there is any hidden secret image. Experimental simulations show that the normalized correlation values between the original cover image and the final visually meaningful cover image are approximately 0.9997. Therefore, the proposed encryption scheme is imperceptible for secret image communications.

In this paper, a new robust and secure video watermarking scheme based on discrete Wavelet Transform (DWT), singular value decomposition (SVD), and Laplacian pyramid is proposed for copyright protection applications. The main contributions of this work are: 1) Increasing watermark robustness towards common signal processing attacks by separating the watermark image into a high-frequency image and a low-frequency image using laplacian pyramid. Then, the singular values of each of the low-frequency watermark image and the high-frequency watermark image are hidden in two different DWT subbands of the original video frame. Separating the watermark and hiding its two parts in two different subbands of the DWT of the video frame makes it robust towards noise, filtering, and compression attacks. 2) Improving the quality of the extracted watermarks via correcting the received watermarked videos using SURF points when those videos are geometrically attacked, mainly by rotation, scaling, and shear attacks. 3) Increasing security and avoiding false positive problems (FPP) associated with SVD by using perceptual image hashing in the proposed scheme. Through experimental results and comparisons to other techniques, the proposed scheme has shown very high imperceptibility for the tested watermarked videos in terms of peak signal to noise ratio (PSNR). Also, the proposed scheme has demonstrated high watermark robustness towards various types of attacks, and an improvement in the quality of the extracted watermarks from 4 to 20 dB compared to other techniques.

In this paper, a robust algorithm of digital image watermarking based on discrete wavelet transform is introduced It uses blind watermarking technique. Digital image watermarking is one such technology that has been developed to protect digital images from illegal manipulations. In particular, digital image watermarking algorithms which are based on the discrete wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets' excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of the human visual system.

A novel image steganography algorithm in wavelet domain is presented using the iterative blending method. Using this algorithm, we can hide a secret image with 256 gray levels into another carrier image. By taking full advantage of the masking characteristics of the human visual system, a JND (just noticeable difference) threshold matrix is given pixel by pixel in the image subbands taking into account the texture and the luminance content of carrier image. The secret image is divided into two matrices to make the gray level no more than 16. Then the matrices are adaptively embedded into the wavelet coefficients of the carrier image by iterative blending. The carrier image and the blending parameter can act as the private keys. The experimental results show that the proposed algorithm provides good transparency and is robust to some extent. The technique also can be used in digital watermarking and other digital application areas.